Delta Live Tables: Getting Started Guide
Build declarative data pipelines with Delta Live Tables—from setup to production deployment.
Delta Live Tables (DLT) lets you build reliable data pipelines with simple SQL or Python. No more manual orchestration—just declare your transformations and let DLT handle the rest.
What are Delta Live Tables?
DLT is a framework for building and managing data pipelines declaratively. You define tables as the output of queries; DLT handles orchestration, compute, and data quality automatically.
Core Concepts
1. Bronze, Silver, Gold
Organize your pipeline into layers: Bronze (raw ingestion), Silver (cleansed), and Gold (aggregated, business-ready). DLT pipelines map naturally to this medallion architecture.
2. Expectations
Add data quality expectations using @expect or @expect_or_fail. Invalid rows can be quarantined or cause the pipeline to fail—you choose.
3. Automatic Schema Evolution
Add or change columns without manual migrations. DLT tracks schema changes and applies them safely.
Your First DLT Pipeline
Create a notebook with SQL or Python. Define your source, apply transformations, and declare target tables. Run the pipeline from the DLT UI or via API. That's it.
Conclusion
Delta Live Tables reduce boilerplate and operational overhead. Start with a simple pipeline, add expectations, and scale from there. For production, combine with Unity Catalogue for governance.
